Multimorbidity, defined as the coexistence of two or more health conditions in an individual, poses an increasing challenge to health systems worldwide. This study employs a network science approach to analyze multimorbidity patterns in Bogotá, Colombia, using administrative health records from 2018. Diagnoses are modeled as nodes, and their co-occurrence is modeled as weighted edges that form networks. Notable structural differences were revealed, as networks in the contributory scheme were larger, denser, and more diverse, while networks in the subsidized scheme were smaller and sparser. This reflects limited diagnostic variety and is potentially linked to reduced access to and continuity of care. Across all groups, chronic conditions such as hypertension, obesity, and dyslipidemia were the most prevalent diagnoses, especially among older adults. Trauma-related comorbidities, including superficial injuries, were more prevalent among men in the subsidized scheme, indicating ongoing exposure to physical risks and deficiencies in long-term management. These findings demonstrate how differences in health system access and organization influence multimorbidity profiles across socioeconomic groups. Multimorbidity networks are a valuable framework for evaluating health system performance because they capture disease interaction structures and identify disparities in care delivery.